Logistic Model Based On The Evaluation Of Listed Manufacturing Companies Probability Of Default

Since the "Basel Ⅲ" the introduction of global financial regulation to re-establish the industry benchmark, this benchmark affect the business model and strategy development banks and financial body, which have increased their regulatory capital standards. That is the nature of capital regulation of risk regulation. Since the main bank’s operating performance by loans to enterprises, thereby forming the principal and interest and the ability to recover the credit formation. Therefore, the credit risk is the biggest risk facing the commercial bank. IRB is one of the core Basel, and calculate the probability of customer default is a key step in the implementation of the IRB approach. Among them, the probability of default means the borrower cannot repay the loan principal and interest future period of time or the possibility of fulfillment of obligations related to the contract requirements. Consider four indicators of risk-weighted assets: the probability of default of enterprises, maturity default risk exposures and exposures. Therefore, the probability of default enterprise research has important practical significance. In addition, the current government to develop "Thirteen Five" plan, clearly put forward to build a new industrial system, accelerate the construction of manufacturing power,the implementation of "Made in China two thousand and twenty-five" strong implementation of industrial engineering group, cultivating a number of strategic industries, accelerate the conduct the development of modern service industry action. This will inevitably result in the development of philosophy alternately rise and fall of different industries, construction manufacturing power, manufacturing as the leading force in the national economy will inevitably bear the brunt. Although the scale of China’s manufacturing enterprises large but weak ability to resist risks. Once the business crisis, the various stakeholders will have a significant impact. The situation is studied manufacturing probability of default just respond to the needs of the current situation, based on this situation, this paper attempts to establish Logistic model to predict the probability of default of China Listed Companies hope this research can have important practical implications for all stakeholders.This paper is divided into five chapters, the first chapter is the introduction, describes the background and significance of this paper, literature review, research, research methods and possible innovation. The second section is an overview of the theory, we introduced the definition, assessment methods and compare the probability of default models, as well as the theoretical framework Logistic model the probability of default of these theories provide theoretical introduction to the empirical section of this article later. The third chapter introduces the construct Logistic model. Selection and Construction introduces explanatoryvariables Logistic model, the company selected study sample, followed by the use of SPSS20.0 software for financial data analysis, based on financial indicators of listed companies, Principal component analysis Principal component selected indicators compare influential of the last model using logistic regression analysis, the model results to determine whether the firm may have a breach, if there is risk of default. The fourth chapter is a prediction of manufacturing firms assess the probability of default. Including selected study sample and data, the main financial indicators chosen ingredients, substituting Logistic model assessment, forecasting the probability of corporate default status of China’s manufacturing industry category. And the outcome and recommendations. The fifth chapter of findings and future prospects. According to the results of empirical analysis, summarized and summarized for each of the banking sector as well as in response to investor demand side risk of default and the company itself establish a financial warning measures put forward suggestions, and directions for future research papers presented better conclusions recommendations.The innovation of this thesis are the following two points:(1) Construction of the Logistic model based on principal component analysis. Based Logistic model, taking into account China’s economic situation in the market for this industry focus attention Combining the company’s financial indicators, innovative analysis of the main components of the proposed financial indicators capability, build a model to assess the probability of default by the test showed that the model strong applicability and relevance.And applied research of China Listed Companies forecast evaluation of the probability of default among.(2) assess the proposed manufacturing-object probability of default. In the manufacturing sector as the research object, according to the Commission in 2012, "Industry Classification of Listed Companies Guidelines" division of manufacturing industries, analyze the possibility of various industries and enterprises in different default. The use of default probability models come in different categories of manufacturing enterprises, analyze the reasons for the manufacturing industry a high probability of default and low probability of default industry may arise, puts forward feasible suggestions for the management and prevention of risk of default listed manufacturing companies.